-
5 Things That Break VKS Clusters in VCF 9 (and How to Fix Them)
Most vSphere Kubernetes Service (VKS) failures in VCF 9 aren’t Kubernetes bugs—they’re infrastructure. Here are the 5 things that break VKS clusters most often and how to diagnose each one fast.
-
How to Upgrade VMware Cloud Foundation (VCF) 9.0 to 9.1: Step-by-Step Guide
Upgrading VMware Cloud Foundation 9.0 to 9.1 is a controlled, full-stack sequence. This step-by-step guide covers the order, prerequisites, and gotchas across VCF Operations, Management Services, SDDC Manager, NSX, vCenter, and ESX.
-
Introducing the AI Infrastructure Sizing & Cost Calculator
Over the past few months, I have been spending a lot of time exploring on AI infrastructure around VMware Private AI, NVIDIA AI Enterprise, RAG, Agentic AI, and AIOps. One question that comes up repeatedly is: “How much infrastructure do we actually need, and what will it cost?” Is there any sizing calculator that we…
-
Framework to Analyze Malicious Behaviour in Cloud Environment using Machine Learning Techniques
Framework to Analyze Malicious Behaviour in Cloud Environment using Machine Learning Techniques | IEEE Conference Publication | IEEE Xplore
-
Security Analysis and Fraud Prevention in Cloud Computing
Security Analysis and Fraud Prevention in Cloud Computing | 38 | The R
-
Behavior Analysis and Crime Prediction using Big Data and Machine Learning
International Journal of Soft Computing and Engineering
-
Data Control in Public Cloud Computing: Issues and Challenges
Data Control in Public Cloud Computing: Issues and Challenges | Bentham Science Publishers
-
Global Best Practices in Early Childhood Education: Comparative Analysis of India and Countries with Advanced ECE Systems
Global Best Practices in Early Childhood Education: Comparative Analysis of India and Countries with Advanced ECE Systems – Pranay Jha, Amrita Jha, 2026
-
Building Enterprise AI with NVIDIA NeMo Microservices: From Data to Guardrails
The GenAI wave is no longer about just calling an LLM API. It’s about building reliable, scalable, secure, and continuously improving AI systems. While many teams are still experimenting with prompts, enterprises are moving toward something bigger: 👉 AI factories powered by microservices And that’s exactly where NVIDIA NeMo comes in. The Big Picture: Enterprise…
-
Performance Comparison while using NVIDIA NIM
When people talk about AI, most of the focus is on models—LLMs, vision models, benchmarks, and capabilities. But in real-world systems, the bigger challenge is not just building or choosing a model. It’s how you run that model efficiently at scale. This is where NVIDIA NIM (NVIDIA Inference Microservices) becomes important. At a simple level,…
-
What is NVIDIA NeMo — and Why It Matters for Agentic AI
When people talk about AI systems, they often focus on models or APIs. But once you move beyond simple use cases, a bigger challenge appears: How do you control, guide, and manage AI behavior in real-world systems? This is where NVIDIA NeMo becomes critical. If NIM is the layer that runs AI models, then NeMo…
-
What is NVIDIA NIM — and Why It Matters for Modern AI Systems
When most people start learning AI, they focus on models—LLMs, vision models, embeddings, and so on. But in real-world systems, models alone are not enough. The real challenge is how to run these models reliably, at scale, and in a way that applications can actually use them. This is exactly where NVIDIA NIM comes into…
Architect’s Toolkit
PJ’s Tools
VMware Cloud Foundation
- VCF Documentation
- VCF 9 Planning & Preparation Workbook
- VCF Bill of Materials (BoM)
- VMware Compatibility Guide
- VMware Interoperability Matrix
- VMware Configuration Maximums
- VMware Ports & Protocols
- VMware Hands-on Labs
- RVTools Download
Nutanix
AI & Cloud-Native Platform
- NVIDIA Build (Model Catalog)
- NVIDIA AI Enterprise Reference Architecture
- NVIDIA NIM Performance Benchmarking
- NVIDIA NGC Catalog
- NeMo Microservices Helm Chart
- Helm Charts Repository
- Hugging Face Models
Architecture & Design
About the Author
Dr Pranay Jha
Dr. Pranay Jha is a Cloud and AI Consultant with 18+ years of experience in hybrid cloud, virtualization, and enterprise infrastructure transformation. He specializes in VMware technologies, multi-cloud strategy, and Generative AI solutions. He holds a PhD in Computer Applications with research focused on Cloud and AI, has published multiple research papers, and has been a VMware vExpert since 2016 and a VMUG Community Leader.
Recommendations & Endorsements
Pranay has very deep technical knowledge and exceptional capabilities. He has strong ability to well-manage complex situations and deliver the customer expectations with high standards of satisfaction. We worked together in one of most complex migration projects and Pranay delivered flawlessly.
Pranay was my VMware Architect on one of our financial accounts at IBM. He was instrumental in documenting and recommending our reference architecture. As a Chief Architect, you are only as good as your team that supports you. Pranay was top notch.
Pranay is proactive, result oriented, responsible and technically sound. Always ready to put all his energy to get the job done. Exceptional troubleshooting skills in Windows Server, virtualization and VMware — a great asset to any company.
Pranay is one of the most talented and dedicated persons I have ever worked with. His vast knowledge from different domains enables him to discuss and help on almost every topic in IT. Needless to say, he is expert of experts in VMware.
DrJha